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Robust optimisation for self-scheduling and bidding strategies of hybrid CSP-fossil power plants

机译:混合式CSP化石电厂自调度和投标策略的鲁棒优化

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This paper describes a profit-maximisation model for a hybrid concentrated solar power (CSP) producer participating in a day-ahead market with bilateral contracts, where there is no correlation between the electricity market price and the solar irradiation. Backup system coordination is included between the molten-salt thermal energy storage (TES) and a fossil-fuel backup to overcome solar irradiation insufficiency, but with emission allowances constrained in the backup system to mitigate carbon footprint. A robust optimisation-based approach is proposed to provide the day-ahead self-schedule under the worst-case realisation of uncertainties due to the electricity market prices and the thermal production from the solar field (SF). These uncertainties are modelled by asymmetric prediction intervals around average values. Additionally, a budget parameter is used to parameterise the degree of conservatism of the decision. The decision provides the optimal bidding strategies consisting in supply functions built not only for different budget parameter values, but also for different emission allowance levels. Finally, a realistic case study is presented to show the effectiveness of the proposed approach.
机译:本文描述了一个混合日光发电(CSP)生产商的利润最大化模型,该生产商通过双边合同参加日间市场,而电价与太阳辐射之间没有相关性。备用系统协调包括在熔融盐热能存储(TES)和化石燃料备用之间,以克服太阳辐射的不足,但在备用系统中限制了排放配额,以减少碳足迹。提出了一种基于优化的鲁棒方法,以在最坏情况下由于电力市场价格和太阳能场(SF)的热量产生而在不确定性最坏情况下提供日程安排。这些不确定性通过平均值附近的不对称预测间隔来建模。另外,预算参数用于参数化决策的保守程度。该决策提供了包括供应函数的最佳投标策略,这些函数不仅针对不同的预算参数值,而且针对不同的排放配额水平。最后,提出了一个现实的案例研究,以证明所提出方法的有效性。

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